I/P Engine, Inc. v. AOL, Inc. et al

Filing 89

Declaration re 88 Memorandum in Support of Margaret Kammerud in Support of Google's Motion to Compel Plaintiff to Provide Conception, Reduction-to-Practice, and Priority Date Infomation for the Patents-in-Suit by Google, Inc.. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E, # 6 Exhibit F, # 7 Exhibit G, # 8 Exhibit H, # 9 Exhibit I, # 10 Exhibit J, # 11 Exhibit K)(Noona, Stephen)

EXHIBIT H

KAUFMAN & CANOLES, P.C.
Stephen E. Noona
[e-mail]
150 West Main Street
Post Office Box 3037
Norfolk, VA 23514
Telephone:
[phone]
Facsimile:
[phone]
QUINN EMANUEL URQUHART & SULLIVAN, LLP
David Bilsker (pro hac vice)
[e-mail]
David A. Perlson (pro hac vice)
[e-mail]
Antonio Sistos (pro hac vice)
[e-mail]
Margaret Kammerud (pro hac vice)
[e-mail]
Joshua Sohn (pro hac vice)
[e-mail]
Jen Ghaussy (pro hac vice)
[e-mail]
50 California Street, 22nd Floor
San Francisco, California 94111
Telephone:
[phone]
Facsimile:
[phone]
Attorneys for Defendants Google Inc., IAC Search
& Media, Inc., Target Corporation, and Gannett
Company, Inc.
UNITED STATES DISTRICT COURT
EASTERN DISTRICT OF VIRGINIA
ALEXANDRIA DIVISION
I/P Engine, Inc.,
Plaintiff,

CASE NO. 2:11-cv-512
DEFENDANTS’ PRELIMINARY
INVALIDITY CONTENTIONS

vs.
AOL, Inc. et al.,
Defendants.

01980.51928/4565579.1

Trial Date:

None set

I.

INTRODUCTION
Defendants Google Inc., IAC Search & Media, Inc., Target Corporation, and Gannett

Company, Inc. (“Defendants”) hereby submit the following Preliminary Invalidity Contentions
to Plaintiff I/P Engine, Inc. (“Plaintiff”).
II.

RESERVATIONS
The information and documents that Defendants produce are provisional and subject to

further revision as follows. Defendants expressly reserve the right to amend the disclosures
herein should Plaintiff provide any information that it failed to provide in its Infringement
Contentions or should Plaintiff amend its infringement contentions in any way. Further, because
Defendants have not yet completed their search for and analysis of relevant prior art, Defendants
reserve the right to revise, amend, and/or supplement the information provided herein, including
identifying and relying on additional references, should Defendants’ further search and analysis
yield additional information or references, consistent with the Federal Rules of Civil Procedure.
Moreover, Defendants reserve the right to revise its ultimate contentions concerning the
invalidity of the claims of the Asserted Patents, which may change depending upon the Court’s
construction of the claims of the Asserted Patents, any findings as to the priority date of the
Asserted Patents, and/or positions that Plaintiff or its expert witness(es) may take concerning
claim interpretation, infringement, and/or invalidity issues.
Prior art not included in this disclosure, whether known or not known to Defendants, may
become relevant. In particular, Defendants are currently unaware of the extent, if any, to which
Plaintiff will contend that limitations of the asserted claims are not disclosed in the prior art
identified by Defendants. To the extent that such an issue arises, Defendants reserve the right to

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identify other references that would have made the addition of the allegedly missing limitation to
the disclosed device or method obvious.
Defendants’ claim charts cite to particular teachings and disclosures of the prior art as
applied to features of the asserted claims. However, persons having ordinary skill in the art
generally may view an item of prior art in the context of other publications, literature, products,
and understanding. As such, the cited portions are only examples, and Defendants reserve the
right to rely on uncited portions of the prior art references and on other publications and expert
testimony as aids in understanding and interpreting the cited portions, as providing context
thereto, and as additional evidence that the prior art discloses a claim limitation. Defendants
further reserve the right to rely on uncited portions of the prior art references, other publications,
and testimony to establish bases for combinations of certain cited references that render the
asserted claims obvious.
The references discussed in the claim charts may disclose the elements of the asserted
claims explicitly and/or inherently, and/or they may be relied upon to show the state of the art in
the relevant time frame. The suggested obviousness combinations are provided in the alternative
to Defendants’ anticipation contentions and are not meant to suggest that any reference included
in the combinations is not by itself anticipatory.
For purposes of these Preliminary Invalidity Contentions, Defendants identify prior art
references and provide element-by-element claim charts based in part on the apparent
constructions of the asserted claims advanced by Plaintiff in its Infringement Contentions.
Nothing stated herein shall be treated as an admission or suggestion that Defendants agree with
Plaintiff regarding either the scope of any of the asserted claims or the claim constructions
advanced by it in its Infringement Contentions or anywhere else. Moreover, nothing in these

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Invalidity Contentions shall be treated as an admission that Defendants’ accused technologies
meet any limitations of the claims.
Depending on the Court’s construction of the claims of the Asserted Patents, and/or
positions that Plaintiff or its expert witness(es) may take concerning claim interpretation,
infringement, and/or invalidity issues, different charted prior art references may be of greater or
lesser relevance and different combinations of these references may be implicated. Given this
uncertainty, the charts may reflect alternative applications of the prior art against the asserted
claims.
Defendants hereby provide disclosures and related documents pertaining only to the
asserted claims as identified by Plaintiff in its Infringement Contentions. Defendants reserve the
right to modify, amend, or supplement these Preliminary Invalidity Contentions to show the
invalidity of any additional claims that the Court may allow Plaintiff to later assert.
III.

PRELIMINARY INVALIDITY CONTENTIONS
The asserted claims of the Asserted Patents are invalid under 35 U.S.C. § 102 and/or §

103 because at least the following prior art references anticipate the claims or render them
obvious, alone or in combination:
Patents or Patent Applications:
U.S. Patent No. 5,835,087 to Herz et al. (“Herz”)
U.S. Patent No. 6,202,058 to Rose et al. (“Rose”)
Publications:
Yezdezard Lashkari, Feature Guided Automated Collaborative Filtering, MIT
Masters Thesis (1995) (“Lashkari”)
David Goldberg et al., Using Collaborative Filtering to Weave an Information
Tapestry, Communications of the ACM (December 1992) (“Goldberg” or
“Tapestry”)

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Marko Balabanovic et al., Fab: Content-Based, Collaborative Recommendation,
Communications of the ACM (March 1997) (“Balabanovic”)
Paul Resnick et al., GroupLens: An Open Architecture for Collaborative filtering
of NetNews, Proceedings of the ACM (1994) (“Resnick” or “GroupLens”)
Shoshana Loeb, “Architecting Personalized Delivery of Multimedia Information,”
Communications of the ACM, December 1992, Vol. 35, No. 12, pp. 39-48
(“Loeb”)
Exemplary claim charts for the claims asserted by Plaintiff are attached as Attachments
A-1 to A-6, and incorporated here. Defendants reserve the right to supplement these contentions
with additional references and charts as Defendants’ investigation continues. Discovery is
ongoing, and Defendants’ prior art investigation and third party discovery is therefore not yet
complete. Defendants reserve the right to present additional items of prior art under 35 U.S.C. §
102(a), (b), (e), (f) and/or (g), and/or § 103 located during the course of discovery or further
investigation. For example, Defendants expect to issue subpoenas to third parties believed to
have knowledge, documentation and/or corroborating evidence concerning some of the prior art
listed in the Interrogatory response and/or additional prior art. These third parties include
without limitation the authors, inventors, or assignees of the references listed in the Interrogatory
response. In addition, Defendants reserve the right to assert invalidity under 35 U.S.C. § 102(c)
or (d) to the extent that discovery or further investigation yield information forming the basis for
such claims.
Based on Defendants' present understanding of the asserted claims of the Asserted
Patents and the constructions that Defendants believe I/P Engine to be asserting based on I/P
Engine's proposed constructions and its infringement contentions, Defendants believe that the
charted references anticipate the claims of the Asserted Patents as shown in the references'
respective charts. However, if the finder of fact determines that some element of a given claim
was not disclosed by an anticipation reference, that reference in combination with the knowledge

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and skill of a person of ordinary skill in the art at the time of the alleged invention and/or other
prior art disclosing the allegedly missing limitations would have rendered each of the asserted
claims obvious.
The Supreme Court has held that the combination of familiar elements according to
known methods is likely to be obvious when it does no more than yield predictable results. KSR
Intl Co. v. Teleflex Inc., 550 U.S. 398, 127 S. Ct. 1727, 1739 (2007). When a work is available
in one field of endeavor, design incentives and other market forces can prompt variations of it,
either in the same field or a different one. Id. at 1740. For the same reason, if a technique has
been used to improve one device, and a person of ordinary skill in the art would recognize that it
would improve similar devices in the same way, using the technique is obvious unless its actual
application is beyond his or her skill. Id.
In order to determine whether there is an apparent reason to combine the known elements
in the fashion claimed by the patent at issue, a court can look to interrelated teachings of multiple
patents; the effects of demands known to the design community or present in the marketplace;
and the background knowledge possessed by a person having ordinary skill in the art. Id. at
1740-41. For example, obviousness can be demonstrated by showing there existed at the time of
invention a known problem for which there was an obvious solution encompassed by the patent's
claims. Id. at 1743. Any need or problem known in the field of endeavor at the time of
invention and addressed by the patent can provide a reason for combining the elements in the
manner claimed. Id. Common sense also teaches that familiar items may have obvious uses
beyond their primary purposes, and in many cases a person of ordinary skill will be able to fit the
teachings of multiple patents together like pieces of a puzzle. Id.

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Thus, the motivation to combine the teachings of the prior art references disclosed herein
is found in the references themselves and/or: (1) the nature of the problem being solved, (2) the
express, implied and inherent teachings of the prior art, (3) the knowledge of persons of ordinary
skill in the art, (4) the fact that the prior art is generally directed towards filtering information
using content-based and collaborative filters, and/or (5) the predictable results obtained in
combining the different elements of the prior art.
Based on Defendants' present understanding of the asserted claims of the Asserted
Patents and the constructions that Defendants believe I/P Engine to be asserting based on I/P
Engine's proposed constructions and its infringement contentions, the asserted claims of the
Asserted Patents are obvious in light of the combinations outlined below. Each of these
combinations yields predictable results.
Any reference or combination of references that anticipates or makes obvious an asserted
independent claim also makes obvious any asserted claim dependent on that independent claim
because every element of each dependent claim was known by a person of ordinary skill at the
time of the alleged invention, and it would have been obvious to combine those known elements
with the independent claims at least as a matter of common sense and routine innovation. For
example, the fact that advertisements can be filtered like any other type of information was wellknown in the art. Also, the fact that passive as well as active feedback data may be used to
gauge user interest in information was well-known in the art. Accordingly, Defendants contend
that each asserted dependent claim is rendered obvious not only by the combinations explicitly
identified in these contentions as rendering a given dependent claim obvious, but also by any
combination of references that renders obvious a claim on which a dependent claim depends.

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Additionally, there are no secondary considerations that might rebut the obviousness of
the Asserted Patents. For instance, the invention(s) disclosed in the Asserted Patents did not
achieve commercial success, as evidenced by the fact that neither the named inventors nor any
other companies that owned the Asserted Patents were able to derive significant revenue through
commercializing these patents. There also was no failure of others to achieve the invention(s) in
the Asserted Patents – to the contrary, as discussed below, numerous prior art systems combined
collaborative and content-based filtering and used these techniques to filter search results
delivered in response to a query. For the same reason, there was no long-felt or unmet need for
the invention(s) in the asserted patents. Additionally, no individual expressed skepticism about
the invention(s) disclosed in the Asserted Patents, nor did these invention(s) garner industry
praise or awards. Finally, neither Defendants nor any other third-party copied the invention(s)
disclosed in the Asserted Patents.
The Asserted Patents (which share a substantially identical specification) explain that it
was well-known in the art how to enter a query into an Internet search engine, obtain search
results through a scanning system, and filter the search results using a content-based filter. See,
e.g., '420 Patent at 1:17-26:
In the operation of the internet, a countless number of information [sic] are available for
downloading from any of at least thousands of sites for consideration by a user at the
user's location. A user typically connects to a portal or other web site having a search
capability, and thereafter enters a particular query, i.e., a request for information relevant
to a topic, a field of interest, etc. Thereafter, the search site typically employs a "spider"
scanning system and a content-based filter in a search engine to search the internet and
find information which match [sic] the query. (emphasis added).
The Asserted Patents purportedly teach how to add a collaborative filter to the scanning
system and content-based filter found in traditional search engines:
In the patent application which is parent to this continuation-in-part application,
i.e. Ser. No. 08/627,436, filed by the present inventors on Apr. 4, 1996, now U.S.
Patent No. 5,867,799 and hereby incorporated by reference, an advanced
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collaborative/content-based information filter system is employed to provide
superior filtering in the process of finding and rating informons which match a
user's query. The information filter structure in this system integrates contentbased filtering and collaborative filtering to determine relevancy of informons
received from various sites in the Internet or other network. ('420 Patent at 1:4656) (emphasis added).
The present invention is directed to an information processing system especially
adapted for use at internet portal or other web sites to make network searches for
information entities relevant to user queries, with collaborative feedback data and
content-based data and adaptive filter structuring, being used in filtering
operations to produce significantly improved search results. ('420 Patent at
2:20:27) (emphasis added).
However, the concept of combining collaborative and content-based filters was wellknown in the prior art.1 For instance, Balabanovic describes the “Fab” system, a “ContentBased, Collaborative Recommendation” system. See Balabanovic at 66. “By combining both
collaborative and content-based filtering systems, Fab may eliminate many of the weaknesses
found in each approach.” Id. Similarly, Rose teaches that “[i]nformation presented to a user via
an information access system is ranked according to a prediction of the likely degree of
relevance to the user's interests . . . The prediction of relevance is carried out by combining data
pertaining to the content of each item of information with other data regarding correlations of
interests between users.” Rose at Abstract. Lashkari discloses “a novel technique for
information filtering that attempts to address the problems faced by both ACF [automated
collaborative filtering] and content-based approaches by combining the two to make use of their
complementary strengths.” Lashkari at 15-16. Herz describes a method under which “[t]he
interest that a given target object X holds for a user U is assumed to be a sum of two quantities:
1

As a threshold matter, the Asserted Patents are entitled to a priority date no earlier than
December 3, 1998 – the filing date of the application that matured into the '420 patent. While
both Asserted Patents claim to be continuations-in-part of U.S. Patent No. 5,867,799 (“the '799
Patent”), they are not entitled to the '799 Patent's earlier priority date. This is because the '799
Patent does not support the claims of the Asserted Patents, at least because the '799 Patent does
not teach searching for or filtering information in response to user queries.

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q(U, X), the intrinsic ‘quality’ of X plus f(U, X), the ‘topical interest’ that users like U have in
target objects like X.” Herz at 18:39-43. And Goldberg describes the “Tapestry” system as
follows: “In addition to content-based filtering, the Tapestry system was designed and built to
support collaborative filtering.” Goldberg at 61 (emphasis in original).
As discussed more specifically below, the elements of each of the asserted claims existed
in the prior art:
A Scanning System for Searching for Information Relevant to a User Query (‘664 Claim
1[a], 38; ‘420 Patent Claim 10[a], 25[a])
As discussed above, the Asserted Patents themselves acknowledge that this element was
found in prior art search engines. In describing typical search engines, the Asserted Patents state
that “[a] user typically connects to a portal or other web site having a search capability, and
thereafter enters a particular query, i.e., a request for information relevant to a topic, a field of
interest, etc. Thereafter, the search site typically employs a ‘spider’ scanning system and a
content-based filter in a search engine to search the internet and find information which match
the query.” '420 Patent at 1:20-26 (emphasis added).
Moreover, several of the prior art references that combine content-based and
collaborative filtering apply these filtering methods to search results of a typical search engine
that has already scanned for information relevant to a user query. For instance, Rose states that
its content-based/collaborative filtering method “is applicable to all different types of
information access systems. For example, it can be employed to filter messages provided to a
user in an electronic mail system and search results obtained through an online text retrieval
service.” Rose at 2:51-55 (emphasis added). Lashkari states that its content-based/collaborative
filter (known as WEBHOUND) can be applied to the results of existing search engines like
Lycos and Yahoo! See Lashkari at 78 (“WEBHOUND is primarily an information filtering

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service. Popular WWW search engines such as Lycos [24], WebCrawler [29], Yahoo [44], etc.
are primarily information retrieval engines (as opposed to information filtering systems). The
two are complementary – a WEBHOUND like front-end to a popular search engine such as
Lycos, could enable users with WEBHOUND accounts to filter the results of their searches on
the extensive databases compiled by these search engines in a personalized fashion.”)
A Feedback System for Receiving Collaborative Feedback Data (‘664 Claim 1[b], 26[b];
‘420 Claim 10[c], 25[c])
The concept of receiving collaborative feedback data to help filter information was wellknown in the prior art. As Resnick explains, with respect the “GroupLens” system,
“[c]ollaborative filters help people make choices based on the opinions of other people.
GroupLens is a system for collaborative filtering of netnews, to help people find articles they
will like in the huge stream of available articles.” Resnick at Abstract. Moreover, as explained
above, numerous other prior art references made use of collaborative feedback in conjunction
with content-based filtering to filter information. See, e.g., Rose at Abstract, Lashkari at 15-16,
Balabanovic at 66, Herz at 18:39-43, Goldberg at 61.
A Content-Based Filter System (“664 Claim 1[c], 26[d]; ‘420 Claim 10[b], 25[b])
As explained immediately above, numerous prior art references employed content-based
filters in conjunction with collaborative filters. See, e.g., Rose at Abstract, Lashkari at 15-16,
Balabanovic at 66, Herz at 18:39-43, Goldberg at 61. Furthermore, the Asserted Patents
themselves acknowledge that content-based filters were commonly used in conjunction with
scanning search engines in the prior art. See '420 Patent at 1:20-26 (“A user typically connects
to a portal or other web site having a search capability, and thereafter enters a particular query,
i.e., a request for information relevant to a topic, a field of interest, etc. Thereafter, the search

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site typically employs a ‘spider’ scanning system and a content-based filter in a search engine to
search the internet and find information which match the query.”) (emphasis added).
Extracting Features from Information (‘664 Claim 21)
The prior art also teaches that the content-based filters may operate by extracting features
from the information to be filtered. See, e.g., Rose at 6:10-25 (“To derive the content-based data,
certain elements of the message, e.g., each word in a document, can be assigned a weight, based
on its statistical importance . . . For non-document types of information, the content data can be
based upon other attributes that are relevant to a user’s interest in that information. For example,
in the movie database, the content vector might take into account the type of movie, such as
action or drama, the actors, its viewer category rating, and the like.”); Lashkari at 16 (“The
technique we present, Feature Guided Automated Collaborative Filtering (FGACF), uses easily
extractable features of items to dynamically partition the domain and so allow ACF [automated
collaborative filtering] to be applied relative to a set of features.”); Herz at 6:18-29 (“The
individual data that describe a target object and constitute the target object’s profile are herein
termed ‘attributes’ of the target object. Attributes may include, but are not limited to, the
following: (1) long pieces of text (a newspaper story, a movie review, a product description or an
advertisement), (2) short pieces of text (name of a movie’s director, name of town from which an
advertisement was placed, name of the language in which an article was written), (3) numeric
representations (price of a product, rating given to a movie, reading level of a book), (4)
associations with other types of objects (list of actors in a movie, list of persons who have read a
document).”)
Obtaining Collaborative Feedback Data that is Passive (‘420 Claim 14, 15, 27, 28)

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The prior art also discloses that the collaborative feedback data may be passive. In other
words, rather than having users actively indicate their interest in certain information, the prior art
teaches how to infer user interest from how the users interact with that information. For
instance, under Herz’s disclosed method, a movie will be deemed more relevant to a given user if
other similar users have implicitly endorsed that movie by renting it. See Herz at 10:44-47. A
purchase that results from an advertisement also leads to an inference of positive relevance
feedback. See id. at 61:4–18. Or under Goldberg’s disclosed method, documents will be
deemed more relevant if they receive replies. See Goldberg at 63. Similarly, Loeb classifies
user feedback as being either “explicit” or “implicit.” See Loeb at 40. Loeb further classifies
users as either “proactive” or “casual,” and notes that implicit or passive means of gathering
feedback are preferable for casual users:
Not all users of information-filtering systems have the same needs and
expectations, and, therefore, they can be classified by the nature of their
information needs and by the way they want to address them. In the two extremes
along this dimension we can distinguish between two types of users, proactive
and casual. The information needs of proactive users are very well defined and
are usually formulated as a query or a profile....In contrast, casual users have
drawn much less attention from information-filtering and retrieval system
designers. Unlike the proactive users, the casual users are not likely to be willing
to engage in lengthy interactions with the system in order to articulate current
information needs and provide explicit feedback. Therefore, automating the
personalized delivery of information to this class of users requires mechanisms
that can cope with this fact. In particular, issues related to mechanisms for the
creation of profiles for new users (e.g., by either using initial profiles based on
stereotypes for users' groups or by building profiles directly from usage data) and
to the detection of implicit feedback (e.g., skipped and revisited items) need
further research.
(Loeb at 41.)
Filtering Advertisement Information (‘664 Claim 5)
It was well-known in the prior art that one specific type of information that may be
presented to users is advertisements. Indeed, advertisements have been presented to consumers

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of information since at least the 19th century. See generally Mark Tungate, AdLand: A Global
History of Advertising at 11-13 (Kogan Page 2007) (describing the use of mass advertising in
Victorian-era newspapers and periodicals). Unsurprisingly, therefore, some of the prior art that
combines content-based and collaborative filtering also explicitly states that these techniques can
be used to filter advertisements. See, e.g., Herz at 61:4-18 (“A consumer who buys a product is
deemed to have provided positive relevance feedback on advertisements for that product, and a
consumer who buys a product apparently because of a particular advertisement (for example, by
using a coupon clipped from that advertisement) is deemed to have provided particularly high
relevance feedback on that advertisement . . . Given a database of such relevance feedback, the
disclosed technology is then used to match advertisements with those users who are most
interested in them . . .”)
* * * * *
Table 1 identifies the claims anticipated by each reference and the attached chart that
identifies specific examples of where each limitation of the anticipated claims is found in that
reference.
Table 1: Prior Art References Anticipating Asserted Claims of the ‘664 and/or ‘420
Patents
Exhibit A Chart

Prior Art

Anticipated Claims

A-1

Rose '058

‘664 Patent: 1, 6, 21, 22, 26,
28, 38
‘420 Patent: 10, 25

A-2

Herz '087

‘664 Patent: 1, 5, 6, 21, 22, 26,
28, 38
‘420 Patent: 10, 14, 15, 25, 27,
28

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A-3

Lashkari, Feature Guided
Automated Collaborative
Filtering

‘664 Patent: 1, 6, 21, 22, 26,
28, 38
‘420 Patent: 10, 25

A-4

Goldberg et al., Using
Collaborative Filtering to
Weave an Information
Tapestry
Balabanovic et al., Fab:
Content-Based, Collaborative
Recommendation

A-5

‘664 Patent: 1, 6, 21, 26, 28,
38

‘664 Patent: 1, 5, 6, 21, 22, 26,
28, 38

‘420 Patent: 10, 14, 15, 25, 27,
28

‘420 Patent: 10, 25
A-6

Resnick et al., GroupLens: An
Open Architecture for
Collaborative Filtering of
NetNews

‘664 Patent: 1, 6, 26, 28, 38
‘420 Patent: 10, 25

The claim charts found in Exhibits A-1 through A-6 also list the combinations of
references that render each claim obvious.
The asserted claims are also invalid under 35 U.S.C. § 112 for non-enablement and
inadequate written description. For example, the Asserted Patents’ specifications describe a
search engine system that uses collaborative and content-based filtering on a set of “wire” or
persistent search results. If there is no “wire” available for a particular query, the described
system issues a “demand” search to a regular search engine. (‘420 Patent, 23:39-53.) The
specification does not describe or disclose using collaborative and content-based filtering with a
“demand” search, however. Plaintiff has apparently interpreted the asserted claims as not
requiring a “wire search.” As the specification does not disclose performing the content-based
and collaborative filtering on the “demand search” rather than the “wire search,” Plaintiff’s
interpretation of the asserted claims would render them invalid for lack of written description.

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Further, the specification does not enable performing collaborative filtering on a demand
search—that is, a search for which users may view different search results rather than the same,
consistent set of search results. Accordingly, Plaintiff’s interpretation of the asserted claims
would also render those claims invalid for lack of enablement.
Each of the asserted claims requires scanning a network for information or depends on
such a claim. ‘420 Patent cl. 10 (“system for scanning a network”); cl. 25 (“scanning a
network”); ‘664 Patent cl. 1 (“scanning system for searching for information”); cl. 26
(“searching for information”). These claims are invalid under 35 U.S.C. § 112 for nonenablement, inadequate written description, and indefiniteness. The Asserted Patents’
specifications’ sole recitation of a scanning system in connection with a user query is that “A
spider system 46C scans a network for a current demand search.” The specifications fail to
disclose a spider system, nor does the specification teach how to build a spider system. “Spider
system” was not a term commonly understood in the art at the time of the purported inventions,
nor is “spider system” defined anywhere in the specifications. The specifications also fail to
disclose how to operate a spider system in connection with a user query.
Additionally, each asserted claim requires “combining” one category of information with
another. The claims are invalid for indefiniteness because one of ordinary skill would not
understand what it means to “combine” information in the context of the claims. Finally, ‘420
Claim 25 and ‘664 Claim 26 recite “receiving collaborative feedback data” or “receiving
information found to be relevant to the query by other users,” but no collaborative feedback
system is recited or disclosed in these claims. Therefore, these claims (and their dependants) are
invalid for indefiniteness.

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Dated: January 24, 2012

By: _/s/ Stephen E. Noona
Stephen E. Noona
KAUFMAN & CANOLES, P.C.
150 West Main Street
Post Office Box 3037
Norfolk, VA 23514
Telephone: [phone]
Facsimile: [phone]
By: _/s/ David Perlson
David Bilsker
David Perlson
Antonio Sistos
Margaret Kammerud
Joshua Sohn
Jennifer Ghaussy
QUINN EMANUEL URQUHART &
SULLIVAN LLP
50 California Street, 22nd Floor
San Francisco, CA 94111
415-875-6600
Telephone: [phone]
Facsimile: [phone]
Counsel for Defendants GOOGLE INC.,
IAC SEARCH & MEDIA, INC., TARGET
CORPORATION, AND GANNETT
COMPANY, INC.

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